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In this paper, we consider the distributed filtering problem for continuous-time stochastic systems over sensor networks subject to Markovian switching topologies. Due to limited communication energy and bandwidth, an event-based communication scheme is proposed with the aim to decrease the transmission frequency. An individual triggering condition is put forward to regulate the communication rates for each component of the system state in order to better reflect the engineering requirements. The aim of this paper is to design a distributed filter over sensor networks with Markovian switching topologies such that the dynamics of the estimation error is exponentially mean-square bounded. It is shown that, with the proposed event-based distributed filtering algorithm, the exponential mean-square boundedness of the estimation errors is guaranteed if the sensor network is distributively detectable and the combined communication topology is strongly connected. A numerical example is presented to illustrate the usefulness of the developed algorithm. [ABSTRACT FROM AUTHOR]

A novel risk-sensitive (RS) control law is proposed for linear systems with stochastic system parameters. RS control laws are efficient means of handling risk in various failures in control caused by stochastic disturbances. However, stochastic parameters invoke problems, resulting controllers may become nonlinear in the state variable and incompatible with linear systems, cannot be obtained in an exact sense, and are defined only on a bounded state region. To solve these problems, this paper presents a risk-sensitive linear (RSL) control method. The important idea is that a standard RS-type cost function is converted to an expectation of a weighted cost function such that the resulting optimal controller is linear in the state. The weight is designed such that the weighted cost function preserves the characteristics of the original RS control. The designed weight allows one to derive the proposed RSL controller whose exact solution is obtained as a linear feedback law for all states. Furthermore, the RSL control law over an infinite horizon guarantees stochastic stability of the feedback system with the control law. The effectiveness of the proposed RSL control law is demonstrated by a numerical simulation. [ABSTRACT FROM AUTHOR]